2016
DOI: 10.1016/j.jphotobiol.2015.12.016
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Efficient detection of internal infestation in wheat based on biophotonics

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Cited by 7 publications
(2 citation statements)
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“…Donné et al (2016) performed segmentation of the corn plant using a convolutional ANN. Shi et al (2016) analyzed losses of quality and quantity of wheat seeds due to insects and created internal infestation detection model by means of pattern recognition techniques. Other technologies and systems of agroclimatic monitoring, systems of monitoring of anomalies through image processing are also employed (Mora et al, 2016).…”
Section: Traditional Technological Strategiesmentioning
confidence: 99%
“…Donné et al (2016) performed segmentation of the corn plant using a convolutional ANN. Shi et al (2016) analyzed losses of quality and quantity of wheat seeds due to insects and created internal infestation detection model by means of pattern recognition techniques. Other technologies and systems of agroclimatic monitoring, systems of monitoring of anomalies through image processing are also employed (Mora et al, 2016).…”
Section: Traditional Technological Strategiesmentioning
confidence: 99%
“…Visual inspection, sampling and sieving are widely used for insect detection in grains (Aspaly et al, 2007). Other methods were developed to detect hidden infestations including staining of kernels to detect eggs, density separation (Shi et al, 2016), x-ray micro-tomography (Toews et al, 2006), acoustical sensors technique (Mankin et al, 2010), near infrared spectroscopy (Perez-Mendoza et al, 2005), Enzyme-Linked Immunosorbent Assay (ELISA) (Dunn et al, 2008) and uric acid analysis (Wehling et al, 1984). The accuracy of these methods depends on insect species, their developmental stage and grain type (Abels and Ludescher, 2003;Dasmahapatra, 2010).…”
Section: Introductionmentioning
confidence: 99%